White Paper: Data and impact on safety in ADAS autonomy

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Written and reviewed by autonomy experts and computer science PhD’s working with Qualcomm’s Automotive Division.

Why read this whitepaper?

We wanted to give you as much value as we could on this topic, so that you can with this whitepaper:

  • Understand how dataset issues become vehicle-level hazards
  • Learn how to detect dataset problems early
  • Gain a structured dataset lifecycle model
  • Reduce costly rework and late-stage debugging
  • Improve auditability and standards compliance

Who should read this whitepaper?

This whitepaper is meant for all senior level autonomy and computer vision practitioners such as:

  • AI Safety / ML Safety Lead
  • ADAS / Autonomous Perception Technical Lead
  • Engineering Director / VP of Autonomy
  • Quality Assurance / Safety Process Manager
  • Head of Functional Safety / FuSa Manager

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